Comparing Connectomes Across Taxa

---

Affinity Testing

Import Connectomes

import numpy as np
import networkx as nx
import matplotlib.pyplot as plt
#from graspologic.plot import heatmap

from grapgh_io import GraphIO

ciona, ciona_e_att, ciona_n_att, ciona_g_att  = GraphIO.load('ciona.json')
fafb, fafb_e_att, fafb_n_att, fafb_g_att = GraphIO.load('fafb.json')
worm, worm_e_att, worm_n_att, worm_g_att = GraphIO.load('worm_wiring_connectome_0_SL.json')

fafb_sides = []

def homophilic_att(graph, name):
    if name == 'ciona':
        for key in graph.edges:
            try:
                if graph.nodes[key[0]]['Side'] == graph.nodes[key[1]]['Side']:
                    graph.edges[key]['Homophilic'] = True
                else:
                    graph.edges[key]['Homophilic'] = False
            except:
                continue

    elif name == 'worm':
        for key in graph.edges:
            try:
                if graph.nodes[key[0]]['attr_dict']['hemisphere'] == graph.nodes[key[1]]['attr_dict']['hemisphere']:
                    graph.edges[key]['Homophilic'] = True
                else:
                    graph.edges[key]['Homophilic'] = False
            except:
                continue
    
    elif name == 'fafb':
        for key in graph.edges:
                if graph.nodes[key[0]]['annotation'][0][-2] == 'L':
                    graph.nodes[key[0]]['Side'] = 'L'
                    if graph.nodes[key[0]]['annotation'][0][-2] == graph.nodes[key[1]]['annotation'][0][-2]:
                        graph.edges[key]['Homophilic'] = True
                        graph.nodes[key[1]]['Side'] = 'L'
                        fafb_sides.append(key[0])
                        fafb_sides.append(key[1])
                    elif graph.nodes[key[0]]['annotation'][0][-2] == 'R':
                        graph.nodes[key[0]]['Side'] = 'R'
                        graph.edges[key]['Homophilic'] = False
                        fafb_sides.append(key[0])
                        fafb_sides.append(key[1])
                    else:
                        graph.edges[key]['Homophilic'] = False
                elif graph.nodes[key[0]]['annotation'][0][-2] == 'R':
                    graph.nodes[key[0]]['Side'] = 'R'
                    if graph.nodes[key[0]]['annotation'][0][-2] == graph.nodes[key[1]]['annotation'][0][-2]:
                        graph.edges[key]['Homophilic'] = True
                        graph.nodes[key[1]]['Side'] = 'R'
                        fafb_sides.append(key[0])
                        fafb_sides.append(key[1])
                    elif graph.nodes[key[0]]['annotation'][0][-2] == 'L':
                        graph.nodes[key[0]]['Side'] = 'L'
                        graph.edges[key]['Homophilic'] = False
                        fafb_sides.append(key[0])
                        fafb_sides.append(key[1])
                    else:
                        graph.edges[key]['Homophilic'] = False
                else:
                    graph.edges[key]['Homophilic'] = False


def homotopic_att(graph, name):
    if name == 'ciona':
        for key in graph.edges:
            try:
                # Originally with cell type, but not enough samples
                if graph.nodes[key[0]]['Brain Region'] == graph.nodes[key[1]]['Brain Region'] and graph.edges[key]['Homophilic'] == False: 
                    graph.edges[key]['Homotopic'] = True
                else:
                    graph.edges[key]['Homotopic'] = False
            except:
                continue
    
    elif name == 'worm':
        for key in graph.edges:
            try:
                if (graph.nodes[key[0]]['attr_dict']['ID'][:-1] == graph.nodes[key[1]]['attr_dict']['ID'][:-1]) and (graph.nodes[key[0]]['attr_dict']['ID'][-1] != graph.nodes[key[1]]['attr_dict']['ID'][-1]) and graph.edges[key]['Homophilic'] == False:
                    graph.edges[key]['Homotopic'] = True
                else:
                    graph.edges[key]['Homotopic'] = False
            except:
                continue

    elif name == 'fafb':
        for key in graph.edges:
            try:
                if (graph.nodes[key[0]]['annotation'][0][:-2] == graph.nodes[key[1]]['annotation'][0][:-2]) and (graph.nodes[key[0]]['annotation'][0][-1] == graph.nodes[key[1]]['annotation'][0][-1]) and graph.edges[key]['Homophilic'] == False:
                    graph.edges[key]['Homotopic'] = True
                else:
                    graph.edges[key]['Homotopic'] = False
            except:
                continue
        



homophilic_att(ciona, 'ciona')
homotopic_att(ciona, 'ciona')

homophilic_att(worm, 'worm')
homotopic_att(worm, 'worm')

homophilic_att(fafb, 'fafb')
homotopic_att(fafb, 'fafb')

# if (worm.nodes[key[0]]['attr_dict']['ID'][-1] == 'L' or worm.nodes[key[0]]['attr_dict']['ID'][-1] == 'R') and (worm.nodes[key[1]]['attr_dict']['ID'][-1] == 'L' or worm.nodes[key[1]]['attr_dict']['ID'][-1] == 'R')

# graph.nodes[key[1]]['annotation'][0][:-1]) and (graph.nodes[key[0]]['attr_dict']['ID'][-1] != graph.nodes[key[1]]['attr_dict']['ID'][-1]) and graph.edges[key]['Homophilic'] == False:

Ex:

worm.edges[(18, 19, 0)]

{'attr_dict': {'weight': 7}, 'Homophilic': False, 'Homotopic': True}

worm.nodes[19]

{'attr_dict': {'ID': 'NSMR',
  'hemisphere': 'right',
  'dorsoventral': None,
  'cell_type0': 'PHARYNX',
  'cell_type1': None}}

worm.nodes[18]

{'attr_dict': {'ID': 'NSML',
  'hemisphere': 'left',
  'dorsoventral': None,
  'cell_type0': 'PHARYNX',
  'cell_type1': None}}

import random

def find_sides(graph, name):
    affinity_nodes = []
    positions = {}
    y_pos = 1
    x_left_pos = -20
    x_right_pos = 20
    for key in graph.nodes:
        try:
            if name == 'ciona' or 'fafb':
                if graph.nodes[key]['Side'] == 'L' :
                    affinity_nodes.append(key)
                    positions[key] = np.asarray([x_left_pos + random.uniform(-5, 5), y_pos])
                elif graph.nodes[key]['Side'] == 'R':
                    affinity_nodes.append(key)
                    positions[key] = np.asarray([x_right_pos + random.uniform(-5, 5), y_pos])
            elif name == 'worm':
                if graph.nodes[key]['attr_dict']['hemisphere'] == 'left' :
                    affinity_nodes.append(key)
                    positions[key] = np.asarray([x_left_pos + random.uniform(-5, 5), y_pos])
                elif graph.nodes[key]['attr_dict']['hemisphere'] == 'right' :
                    affinity_nodes.append(key)
                    positions[key] = np.asarray([x_right_pos + random.uniform(-5, 5), y_pos])
            

            y_pos += 1

        except:
            y_pos += 1
            continue

    return affinity_nodes, positions

ciona_sides, ciona_coors = find_sides(ciona, 'ciona')

worm_sides, worm_coors = find_sides(worm, 'worm')

fafb_sides, fafb_coors = find_sides(fafb, 'fafb')

Visualize Each

Ciona

#Ciona: Homophilic in White, Non-Homophilic in Black
#Left hemisphere on the left, right on the right

edge_colors = []
for line in nx.generate_edgelist(ciona.subgraph(ciona_sides), data=False):
    edge = []
    edge.append(line.rsplit(' ', 1)[0])
    edge.append(line.rsplit(' ', 1)[1])
    edge = tuple(edge)
    
    if ciona.subgraph(ciona_sides).edges[edge]['Homophilic']:
        edge_colors.append("white")
    else:
        edge_colors.append("black")

fig = plt.figure(figsize=(5, 5))
ax = fig.add_subplot(1, 1, 1) # nrows, ncols, index
ax.set_facecolor((0.5, 0, 0))
nx.draw_networkx(ciona.subgraph(ciona_sides), pos=ciona_coors, node_size=20, with_labels=False, width=0.25, arrowsize=5, edge_color=edge_colors) #, nodelist=ciona_sides

#Ciona: Non-Homotopic in White, Homotopic in Black
#Left hemisphere on the left, right on the right

edge_colors = []
for line in nx.generate_edgelist(ciona.subgraph(ciona_sides), data=False):
    edge = []
    edge.append(line.rsplit(' ', 1)[0])
    edge.append(line.rsplit(' ', 1)[1])
    edge = tuple(edge)
    
    if ciona.subgraph(ciona_sides).edges[edge]['Homotopic']:
        edge_colors.append("black")
    else:
        edge_colors.append("white")

fig = plt.figure(figsize=(5, 5))
ax = fig.add_subplot(1, 1, 1) # nrows, ncols, index
ax.set_facecolor((0.5, 0, 0))
nx.draw_networkx(ciona.subgraph(ciona_sides), pos=ciona_coors, node_size=20, with_labels=False, width=0.25, arrowsize=5, edge_color=edge_colors) #, nodelist=ciona_sides

Worm

#Worm: Homophilic in White, Non-Homophilic in Black
#Left hemisphere on the left, right on the right

edge_colors = []
for edge in worm.subgraph(worm_sides).edges:

    if worm.subgraph(worm_sides).edges[edge]['Homophilic']:
        edge_colors.append("white")
    else:
        edge_colors.append("black")

fig = plt.figure(figsize=(5, 5))
ax = fig.add_subplot(1, 1, 1) # nrows, ncols, index
ax.set_facecolor((0.5, 0, 0))
nx.draw_networkx(worm.subgraph(worm_sides), pos=worm_coors, node_size=20, with_labels=False, width=0.25, arrowsize=5, edge_color=edge_colors) #, nodelist=ciona_sides

#Worm: Non-Homotopic in White, Homotopic in Black
#Left hemisphere on the left, right on the right

edge_colors = []
for edge in worm.subgraph(worm_sides).edges:

    if worm.subgraph(worm_sides).edges[edge]['Homotopic']:
        edge_colors.append("black")
    else:
        edge_colors.append("white")

fig = plt.figure(figsize=(5, 5))
ax = fig.add_subplot(1, 1, 1) # nrows, ncols, index
ax.set_facecolor((0.5, 0, 0))
nx.draw_networkx(worm.subgraph(worm_sides), pos=worm_coors, node_size=20, with_labels=False, width=0.25, arrowsize=5, edge_color=edge_colors) #, nodelist=ciona_sides

FAFB

#Fafb: Homophilic in White, Non-Homophilic in Black
#Left hemisphere on the left, right on the right

edge_colors = []
for line in nx.generate_edgelist(fafb.subgraph(fafb_sides), data=False):
    edge = []
    edge.append(int(line.rsplit(' ', 1)[0]))
    edge.append(int(line.rsplit(' ', 1)[1]))
    edge = tuple(edge)
    
    if fafb.subgraph(fafb_sides).edges[edge]['Homophilic']:
        edge_colors.append("white")
    else:
        edge_colors.append("black")

fig = plt.figure(figsize=(5, 5))
ax = fig.add_subplot(1, 1, 1) # nrows, ncols, index
ax.set_facecolor((0.5, 0, 0))
nx.draw_networkx(fafb.subgraph(fafb_sides), pos=fafb_coors, node_size=20, with_labels=False, width=0.25, arrowsize=5, edge_color=edge_colors) #, nodelist=ciona_sides

#Fafb: Non-Homotopic in White, Homotopic in Black
#Left hemisphere on the left, right on the right

edge_colors = []
for line in nx.generate_edgelist(fafb.subgraph(fafb_sides), data=False):
    edge = []
    edge.append(int(line.rsplit(' ', 1)[0]))
    edge.append(int(line.rsplit(' ', 1)[1]))
    edge = tuple(edge)
    
    if fafb.subgraph(fafb_sides).edges[edge]['Homotopic']:
        edge_colors.append("black")
    else:
        edge_colors.append("white")

fig = plt.figure(figsize=(5, 5))
ax = fig.add_subplot(1, 1, 1) # nrows, ncols, index
ax.set_facecolor((0.5, 0, 0))
nx.draw_networkx(fafb.subgraph(fafb_sides), pos=fafb_coors, node_size=20, with_labels=False, width=0.25, arrowsize=5, edge_color=edge_colors) #, nodelist=ciona_sides

!jupyter nbconvert --to html Affinity_Testing.ipynb

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